The massive amount of data generated on the internet, social media, and mobile phones today is making organizations sit-up and devise ways to use this information to improve customer experience. Organizations are increasingly relying on customer data spread over these disparate sources and their own internal database to create personalized offerings.

The magic lies not in collecting vast amounts of data but in its accurate analysis for customer trends and arriving at a personalized offering that wows the customer.

Online retailers have throughout been pushing the envelope with functionalities like suggesting products other customers with similar interests bought, suggesting products you had previously shortlisted, sharp imagery and visuals of the product, same day deliveries, and the list goes on.

However, traditional brick-and-mortar retailers are embracing big data too and coming up with innovative offers and a truly omni-channel strategy to make the customer spend that rupee at their store. A number of traditional retail stores now have online presence and are integrating their digital presence with the physical to come up with innovative and convenient ways to delight customers. E.g.: Enabling an online purchaser with the option of returning the merchandise at the nearest retail outlet, or enabling a purchaser to check availability of the product online and hold the product at the nearest store to pick it up personally.

Traditional retailers are working to provide the same advantages and comfort that online browsing offers, at the physical store. For instance, setting up huge digital screens at the POS that carry high quality images of what the customer is looking for and allowing him to browse through colors, variants and sizes instead of having to look through physical inventory. Brick-and-mortar outlets are ensuring that no stone is left unturned in matching the convenience that online shopping offers.

A furniture retailer created an application/planner on their website that would enable shoppers to upload images of their rooms and be able to move/arrange furniture to visualize the room with the selected furniture.

The retailer also created a section on the website that made personalized product suggestions to shoppers based on their browsing and purchase history. Finally, the retailer provided his sales personnel with hand held devices loaded with information on the customer’s historical purchase patterns and current needs. This enabled them to efficiently handle all customer queries thus increasing the probability of the sale.

Buy now, pay later – I trust Big Data

Not willing to lose out on the revenue opportunity arising from customers changing their mind about a purchase at the last minute, or the payment gateway taking too long, a start-up leveraged technology to find solutions to improve the checkout process.

Just purchase, and pay later. Customers were only required to provide their name, shipping address, and email address, the latter to receive payment instructions. Customers are required to complete payment within two weeks of receiving the merchandise.

The retailer uses an algorithm with over 200 parameters to calculate risk. The parameters include previous purchases, normal time of the day the customer makes purchases, frequency of purchases, and even how the customer types his name.

By analyzing patterns on each shopper, coupled with academic research, public information, and general transaction analysis, the retailer tries to find anomalies in the transaction. For instance, in the case of an old lady trying to purchase gym equipment at 2 in the morning, the retailer asked the customer to provide additional information or call the support center to complete the purchase cycle.

Technologies like Big Data have provided retailers with limitless opportunities to understand their customers better and almost predict what they intend to buy. All this is based on a historical analysis of the customer’s purchase patterns and accordingly what he is likely to purchase next. Include the customer’s social media updates on what products he likes and if any special occasion – marriage, anniversary etc. – coming up and the data analysis is quite accurately able to prompt the customer’s next purchase.

Further, mobile apps enable knowledge on the customer’s location and allow for geo based targeting of specific promotional offers to the customer’s smartphone when he is in the store’s vicinity. What was a possible ‘just looking’ visit acquires a high likelihood of purchase.

Thus, the ability to collect and analyze large amount of customer data from disparate sources has empowered retailers to identify customer purchase pattern and devise offerings that appeal the most to the customer – making it an almost intuitive sale. Big Data has made possible this scenario and only those retailers who leverage this will continue to move with the times and stay relevant.